Triple
T6389025
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Waimakariri District |
E143771
|
entity |
| Predicate | containsSettlement |
P847
|
FINISHED |
| Object |
Cust
Cust is a small rural township in New Zealand’s Canterbury region, known for its agricultural surroundings and close-knit community.
|
E589775
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Cust | Statement: [Waimakariri District, containsSettlement, Cust]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cust Context triple: [Waimakariri District, containsSettlement, Cust]
-
A.
COS
COS is the French Armed Forces' elite joint command responsible for planning and conducting special operations.
-
B.
COS
COS is a Hubble Space Telescope instrument designed to study the origins and evolution of the universe by analyzing the ultraviolet light from distant astronomical objects.
-
C.
COS
COS is the College of Science at Northeastern University, encompassing disciplines such as biology, chemistry, physics, mathematics, and related scientific fields.
-
D.
CST
CST is the time zone used throughout mainland China, eight hours ahead of Coordinated Universal Time (UTC+8).
-
E.
CST
CST is a prominent Chicago-based theater company renowned for its innovative productions of Shakespearean and other classic and contemporary works.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Cust Triple: [Waimakariri District, containsSettlement, Cust]
Generated description
Cust is a small rural township in New Zealand’s Canterbury region, known for its agricultural surroundings and close-knit community.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Cust Target entity description: Cust is a small rural township in New Zealand’s Canterbury region, known for its agricultural surroundings and close-knit community.
-
A.
COS
COS is the French Armed Forces' elite joint command responsible for planning and conducting special operations.
-
B.
COS
COS is the College of Science at Northeastern University, encompassing disciplines such as biology, chemistry, physics, mathematics, and related scientific fields.
-
C.
COS
COS is a Hubble Space Telescope instrument designed to study the origins and evolution of the universe by analyzing the ultraviolet light from distant astronomical objects.
-
D.
CST
CST is the abbreviation for the Communications Security Establishment, Canada’s national cryptologic agency responsible for foreign signals intelligence and cybersecurity.
-
E.
CST
CST is the National Rail station code for London Cannon Street railway station in central London.
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69c008dac1ec81909cef8157ccd69962 |
completed | March 22, 2026, 3:20 p.m. |
| NER | Named-entity recognition | batch_69c0686b4f34819088ff07185b34e536 |
completed | March 22, 2026, 10:08 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6388224fc8190aabd6e6d75887367 |
completed | March 27, 2026, 7:57 a.m. |
| NEDg | Description generation | batch_69c6397756c481909ca13339c2186c0a |
completed | March 27, 2026, 8:01 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69c63a0a4a108190b474555d8cb1540c |
completed | March 27, 2026, 8:04 a.m. |
Created at: March 22, 2026, 4:34 p.m.